A population‐based temporal logic gate for timing and recording chemical events

Engineered bacterial sensors have potential applications in human health monitoring, environmental chemical detection, and materials biosynthesis. While such bacterial devices have long been engineered to differentiate between combinations of inputs, their potential to process signal timing and duration has been overlooked. In this work, we present a two‐input temporal logic gate that can sense and record the order of the inputs, the timing between inputs, and the duration of input pulses. Our temporal logic gate design relies on unidirectional DNA recombination mediated by bacteriophage integrases to detect and encode sequences of input events. For an E. coli strain engineered to contain our temporal logic gate, we compare predictions of Markov model simulations with laboratory measurements of final population distributions for both step and pulse inputs. Although single cells were engineered to have digital outputs, stochastic noise created heterogeneous single‐cell responses that translated into analog population responses. Furthermore, when single‐cell genetic states were aggregated into population‐level distributions, these distributions contained unique information not encoded in individual cells. Thus, final differentiated sub‐populations could be used to deduce order, timing, and duration of transient chemical events.     

An innovative approach for testing bioinformatics programs using metamorphic testing

Background  

Recent advances in experimental and computational technologies have fueled the development of many sophisticated bioinformatics programs. The correctness of such programs is crucial as incorrectly computed results may lead to wrong biological conclusion or misguide downstream experimentation. Common software testing procedures involve executing the target program with a set of test inputs and then verifying the correctness of the test outputs. However, due to the complexity of many bioinformatics programs, it is often difficult to verify the correctness of the test outputs. Therefore our ability to perform systematic software testing is greatly hindered.     

Growth of yeasts, lactic and acetic acid bacteria in palm wine during tapping and fermentation from felled oil palm (Elaeis guineensis) in Ghana

AIM: To investigate the microbiological and biochemical changes which occur in palm wine during the tapping of felled oil palm trees. METHODS AND RESUlts: Microbiological and biochemical contents of palm wine were determined during the tapping of felled oil palm trees for 5 weeks and also during the storage. Saccharomyces cerevisiae dominated the yeast biota and was the only species isolated in the mature samples. Lactobacillus plantarum and Leuconostoc mesenteroides were the dominated lactic acid bacteria, whilst acetic acid bacteria were isolated only after the third day when levels of alcohol had become substantial. The pH, lactic and acetic acid concentrations during the tapping were among 3.5-4.0%, 0.1-0.3% and 0.2-0.4% respectively, whilst the alcohol contents of samples collected within the day were between 1.4% and 2.82%; palm wine which had accumulated over night, 3.24% to 4.75%; and palm wine held for 24 h, over 7.0%. CONCLUSION: Accumulation of alcohol in palm wine occurs in three stages during the tapping and marketing with the concurrent lactic and acetic acid fermentation taking place as well. SIGNIFICANCE AND IMPACT OF THE STUDY: Yeasts, lactic and acetic acid bacteria are all important in the fermentation of palm wine and influence the composition of the product.     

Utilization of Unfermented Cassava Flour for the Production of an Indigenous African Fermented Food, Agbelima

Summary Unfermented cassava flour, also called high quality cassava flour (HQCF) is used as a partial substitute for wheat flour in the baking industry. This work was carried out to produce an indigenous fermented cassava dough, agbelima, from high quality cassava flour in order to diversify uses for the flour. An isolate of each of the dominant species of lactic acid bacteria isolated from agbelima, was used to ferment reconstituted HQCF dough into agbelima, whilst pH changes, population on MRS, and the organoleptic quality were assessed. The antimicrobial properties of the fermenting samples against three enteric pathogens were also investigated. Lactobacillus plantarum, Lactobacillus brevis, Lactobacillus fermentum and Leuconostoc mesenteroides were isolated at levels of 10¹⁰, 10⁹, 10⁹ and 10⁸ c.f.u. g⁻¹ respectively in agbelima. All isolates and a control sample, produced agbelima with pH of between 4.11 and 3.82 in 48 h, and ANOVA showed no significant difference between the pH of the samples at P ≤ 0.05. Spontaneous fermentation of the reconstituted dough was possible, because the flour was found to contain Lactobacillus plantarum at a level of 10⁶ c.f.u. g⁻¹ as well as the other species isolated from agbelima. Counts of Gram-positive catalase-negative rods and cocci on MRS in all the fermented samples were at levels of 10⁸ to 10⁹ c.f.u. g⁻¹, with ANOVA showing no significant difference between the populations at P ≤ 0.05. Three enteric pathogens, Salmonella typhimurium 9, Echerichia coli D2188 and Vibrio cholerae C-230, inoculated into the samples at 10⁶ to 10⁷ c.f.u. g⁻¹ at the start of fermentation, could not be detected in 10 g of any of the samples at the end of 48 h fermentation. A taste panel preferred banku - a stiff porridge made from a combination of fermented maize dough and fermented cassava dough – prepared with fermented HQCF dough to banku prepared with a market sample of agbelima or reconstituted agbelima flour. Processing the highly perishable cassava roots into high quality cassava flour, therefore, offers a means for preserving cassava, which can subsequently be used for both industrial and traditional purposes.     

The contribution of moulds and yeasts to the fermentation of 'agbelima' cassava dough

Agbelima, a fermented cassava meal widely consumed in Ghana, Togo and Benin, is produced by fermenting grated cassava with one of several types of traditional cassava dough inoculum. During fermentation a smooth textured sour dough is produced, the toxicity of cassava is reduced and there is a build up of volatile aroma compounds. Four types of inocula were included in the present investigation. In one type moulds were found to form a dominant part of the microbiota, the species present being Penicillium sclerotiorum, P. citrinum, P. nodulum, Geotrichum candidum and a basidiomycete. All these moulds were found to possess cellulase activity which was responsible for the hydrolysis of cassava tuber cellulose during fermentation leading to a breakdown of the coarse texture of cassava dough. The yeasts Candida krusei, C. tropicalis and Zygosaccharomyces spp. were present in high numbers in the four types of inocula including themouldy inoculum. The yeasts C. tropicalis and some strains of Zygosaccharomyces, all ofwhich possessed cellulase activity, were also found to contribute to the modification of cassavatexture during fermentation. All yeasts and moulds exhibited linamarase activity and were therefore capable of breaking down the cyanogenic glucosides present in cassava.     

A genetic ensemble approach for gene-gene interaction identification

Background  

It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging.     

Gene-gene interaction filtering with ensemble of filters

BACKGROUND: Complex diseases are commonly caused by multiple genes and their interactions with each other. Genome-wide association (GWA) studies provide us the opportunity to capture those disease associated genes and gene-gene interactions through panels of SNP markers. However, a proper filtering procedure is critical to reduce the search space prior to the computationally intensive gene-gene interaction identification step. In this study, we show that two commonly used SNP-SNP interaction filtering algorithms, ReliefF and tuned ReliefF (TuRF), are sensitive to the order of the samples in the dataset, giving rise to unstable and suboptimal results. However, we observe that the 'unstable' results from multiple runs of these algorithms can provide valuable information about the dataset. We therefore hypothesize that aggregating results from multiple runs of the algorithm may improve the filtering performance. RESULTS: We propose a simple and effective ensemble approach in which the results from multiple runs of an unstable filter are aggregated based on the general theory of ensemble learning. The ensemble versions of the ReliefF and TuRF algorithms, referred to as ReliefF-E and TuRF-E, are robust to sample order dependency and enable a more informative investigation of data characteristics. Using simulated and real datasets, we demonstrate that both the ensemble of ReliefF and the ensemble of TuRF can generate a much more stable SNP ranking than the original algorithms. Furthermore, the ensemble of TuRF achieved the highest success rate in comparison to many state-of-the-art algorithms as well as traditional χ2-test and odds ratio methods in terms of retaining gene-gene interactions.